Anomaly Detection

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Overview

Anomaly detection studies how to identify observations or events that depart from expected behavior, often when examples of real anomalies are scarce or unknown. Common approaches learn normality through density estimation, isolation methods, reconstruction or forecasting, while newer methods use graph structure, multimodal features, synthetic anomalies, and pretrained vision or language models. Work spans settings such as industrial images, sensor time series, network traffic, and transaction graphs, with benchmarks including MVTec AD, SWaT, and DCASE used to assess detection and localization. A central challenge is balancing sensitivity against false alarms as data shift, training sets become contaminated, and models move from curated benchmarks to constrained real-world deployments.

Latest papers

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657 papers61 papers in the last four weeks, level with the four weeks before. 0.4% of all new papers.

  1. Weakly-Supervised Spatiotemporal Anomaly Detection

    May 13, 2026Urvi Gianchandani, Praveen Tirupattur, Mubarak ShahAnomaly LocalizationWeakly Supervised Video Anomaly Detection

    University of Texas at Dallas · University of Central Florida

  2. Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with 'nonconform'

    May 13, 2026Oliver Hennhöfer, Maximilian Kirsch, Christine PreisachFDR ControlConformal Prediction

    Intelligent Systems Research Group, Karlsruhe University of Applied Sciences

  3. Learning Feature Encoder with Synthetic Anomalies for Weakly Supervised Graph Anomaly Detection

    May 12, 2026Yingjie Zhou, Yuqin Xie, Fanxing Liu +3Graph Representation LearningAnomaly Detection

    Sichuan University, Chengdu 610065, China · University of Connecticut, Storrs, CT 06269, USA · University of Electronic Science and Technology of China, Chengdu 611731, China +1

  4. Conditional anomaly detection methods for patient-management alert systems

    May 11, 2026Michal Valko, Gregory Cooper, Amy Seybert +3Clinical Decision SupportAnomaly Detection

    University of Pittsburgh, PA

  5. Hypergraph-Enhanced Training-Free and Language-Free Few-Shot Anomaly Detection

    May 11, 2026Guohuan Xie, Xin He, Dingying Fan +2Few-Shot Anomaly DetectionMedical Image Anomaly Detection

    Nankai University · Tianjin University of Technology · Tsinghua University

  6. AnomalyClaw: A Universal Visual Anomaly Detection Agent via Tool-Grounded Refutation

    May 11, 2026Xi Jiang, Yinjie Zhao, Zesheng Yang +1Tool-Using Vision-Language AgentsVLM Reasoning

    Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China · School of EEE, Nanyang Technological University (NTU), Singapore · CFAR, Agency for Science, Technology and Research (A*STAR), Singapore

  7. When Normality Shifts: Risk-Aware Test-Time Adaptation for Unsupervised Tabular Anomaly Detection

    May 11, 2026Wei Huang, Hezhe Qiao, Kailai Zhang +3Test-Time AdaptationTabular Anomaly Detection

  8. Multi-Tier Labeling and Physics-Informed Learning for Orbital Anomaly Detection at Scale

    May 10, 2026Yong FuWeakly Supervised LearningPhysics-Informed ML

    Substratum Labs, Inc.

  9. FragBench: Cross-Session Attacks Hidden in Benign-Looking Fragments

    May 10, 2026Astha Mehta, Niruthiha Selvanayagam, Cedric Lam +10LLM Safety BenchmarksLanguage Model Safety Evaluation

    Isabella · ÉTS Montreal / SPAR · Mila / Lida Safety

  10. FedCIGAR: A Personalized Reconstruction Approach for Federated Graph-level Anomaly Detection

    May 10, 2026Yunfeng Zhao, Yixin Liu, Qingfeng Chen +3Federated Graph LearningReconstruction-Based Anomaly Detection

    Guangxi University · Griffith University

  11. Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation

    May 9, 2026Lei Ma, Suhani Chaudhary, Ethan Shanbaum +5Online Anomaly DetectionInterpretable Anomaly Detection

    Worcester Polytechnic Institute, USA · UC Riverside, USA · University of Nevada, Las Vegas, USA

  12. The Payment Heterogeneity Index: An Integrated Unsupervised Framework for High-Volume Procurement Oversight and Decision Support

    May 9, 2026Kyriakos ChristodoulidesUnsupervised Anomaly DetectionAnomaly Detection

    Philips University, Department of Computer Science, Nicosia, Cyprus · Novel Intelligence, London, UK

  13. ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage

    May 9, 2026Wenbo Gao, Songbai Tan, Zhongan Wang +6Online Anomaly DetectionFinancial Fraud Detection

    Harbin Institute of Technology, Shenzhen · Shenzhen University · Zhejiang University +4

  14. Outlier detection for patient monitoring and alerting

    May 9, 2026Miloš Hauskrecht, Iyad Batal, Michal Valko +3HealthcareClinical Decision Support

    Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, USA · The Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA · Inria Lille-Nord Europe, equipe SequeL, Lille, France +2

  15. Seeing the Needle in the Haystack: Towards Weakly-Supervised Log Instance Anomaly Localization via Counterfactual Perturbation

    May 9, 2026Yutszyuk Wong, Wentai Wu, Yuen-Ying Yeung +1Online Anomaly DetectionAnomaly Localization

    Jinan University · Guangzhou, China · South China University of Technology

  16. Contour-Native Bridge Defect Detection and Compact Digital Archiving with Frequency-Supervised Fourier Contours

    May 9, 2026Jin Liu, Wang Wang, Hongxu Pu +4Frequency-Domain Image ProcessingStructural Health Monitoring

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430072, China · Sustainability X-Lab, The University of Hong Kong, Hong Kong, China · Department of Cyber Security, Southeast University, No. 2, Southeast University Road, Nanjing, 211102, China +2

  17. Simultaneous Monitoring of Shape and Surface Color via 4D Point Clouds: A Registration-free Approach

    May 9, 2026Mariafrancesca Patalano, Giovanna Capizzi, Kamran PaynabarPoint Cloud Anomaly DetectionAnomaly Localization

    Department of Statistical Sciences, University of Padua · School of Industrial and Systems Engineering, Georgia Institute of Technology

  18. GRASP -- Graph-Based Anomaly Detection Through Self-Supervised Classification

    May 8, 2026Robin Buchta, Carsten Kleiner, Felix Heine +1CybersecurityAnomaly Detection

  19. A Task-Agnostic Algebraic Integrity Metric for Event-Camera Streams Toward SOTIF-Compliant Perception using Pearson Correlation Coefficient

    May 8, 2026Arthur de Miranda NetoEvent-Based VisionAutonomous Driving Perception

    Federal University of Lavras (UFLA), Brazil

  20. GESR: Graph-Based Edge Semantic Reconstruction for Stealthy Communication Detection with Benign-Only Training

    May 8, 2026Henghui Xu, Yuchen Zhang, Xiaobo MaNetwork Intrusion DetectionReconstruction-Based Anomaly Detection

    MOE Key Laboratory for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, China · Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China · Shaanxi Province Key Laboratory of Computer Network, Xi’an Jiaotong2026 University, Xi’an, China

  21. HBEE: Human Behavioral Entropy Engine -- Pre-Registered Multi-Agent LLM Simulation of Peer-Suspicion-Based Detection Inversion

    May 8, 2026Vickson FerrelLLMs for CybersecurityAnomaly Detection

    Faculty of Computer Science & Information Technology Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Malaysia · Founder & Lead Architect, Vixero Technology Enterprise, Kuching, Sarawak, Malaysia

  22. Real-IAD MVN: A Multi-View Normal Vector Dataset and Benchmark for High-Fidelity Industrial Anomaly Detection

    May 8, 2026Wenbing Zhu, Jianing Liang, Linjie Cheng +7Industrial Anomaly DetectionMultimodal Anomaly Detection

    1Fudan University · 4Rongcheer Co., Ltd. · 3Donghua University +1

  23. GAD in the Wild: Benchmarking Graph Anomaly Detection under Realistic Deployment Challenges

    May 8, 2026Jingjing Zhou, Shiyu Huang, Qing Qing +7Graph Neural NetworksGraph Representation Learning

    Zhejiang Gongshang University · Jilin University · Adelaide University +2

  24. Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection

    May 7, 2026Victor Livernoche, Jie Zan, Reihaneh RabbanyTabular Anomaly DetectionUnsupervised Anomaly Detection

    McGill University, Mila, Montréal, Canada

  25. Smart Railway Obstruction Detection System using IoT and Computer Vision

    May 7, 2026Pravin Kumar, Mritunjay Shall Peelam, Ramakant Kumar +2Internet of ThingsAnomaly Detection

    School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, 248001, Uttarakhand, India · Department of Computer Science, Galgotias College of Engineering & Technology · Department of Computer Science, NIT Jamshedpur +2

  26. Conditional outlier detection for clinical alerting

    May 6, 2026Milos Hauskrecht, Michal Valko, Shyam Visweswaran +3HealthcareClinical Decision Support

    Computer Science Department · Department of Biomedical Informatics · Department of Critical Care Medicine

  27. Evidence-based anomaly detection in clinical domains

    May 6, 2026Milos Hauskrecht, Michal Valko, Branislav Kveton +2Clinical Decision SupportClinical Decision-Making

    Computer Science Department; 2 Intelligent Systems Program; 3 Department of Biomedical Informatics, University of Pittsburgh, PA · Intelligent Systems Program; 3 Department of Biomedical Informatics, University of Pittsburgh, PA

  28. CCL-D: A High-Precision Diagnostic System for Slow and Hang Anomalies in Large-Scale Model Training

    May 6, 2026Yida Gu, Fakang Wang, Jianhao Fu +17Anomaly LocalizationDistributed Training

    University of Chinese Academy of Sciences · Ant Group · Jilin University

  29. Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning

    May 5, 2026Michal ValkoGraph-Based Semi-Supervised LearningSemi-Supervised Learning

    Comenius University, Bratislava · University of Pittsburgh

  30. MEMSAD: Gradient-Coupled Anomaly Detection for Memory Poisoning in Retrieval-Augmented Agents

    May 5, 2026Ishrith GowdaRAG Poisoning AttacksAgent Memory Poisoning

    University of California, Berkeley · Department of Electrical Engineering and Computer Sciences University of California, Berkeley · Work conducted at the Song Lab, Berkeley AI Research, University of California, Berkeley.